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Prior Authorization Review PanelMCO Policy Submission
A separate copy of this form must accompany each policy submitted for review.Policies submitted without this form will not be considered for review.
Plan: Aetna Better Health Submission Date: 11/01/2018
Policy Number: 0664 Effective Date: Revision Date:
Policy Name: Signal-Averaged Electrocardiography(SAECG)
Type of Submission – Check all that apply: New Policy* Revised Policy Annual Review – No Revisions
*All revisions to the policy must be highlighted using track changes throughout the document. Please provide any clarifying information for the policy below:
CPB 0664 Signal-Averaged Electrocardiography (SAECG)
Policy is new to Aetna Better Health of Pennsylvania.
Name of Authorized Individual (Please type or print):
Dr. Bernard Lewin, M.D.
Signature of Authorized Individual:
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Signal-Averaged Electrocardiography (SAECG) - Medical Clinical Policy Bulletins | Aetna Page 1 of 17
Signal-Averaged Electrocardiography (SAECG)
Policy History
Last Review: 11/16/2017
Effective: 05/02/2003
Next Review: 07/12/2018
Review History
Definitions
Additional
Information
Clinical Policy Bulletin
Notes
Number: 0664
Policy
*Please see amendment forPennsylvaniaMedicaid
at theend of this CPB.
Aetna considers signal-averaged electrocardiography
experimental and investigational because no prospective
clinical studies have demonstrated the utility of this testing in
improving clinical outcomes.
Aetna considers remote algorithmic analysis of
electrocardiographic-derived data (Premier
Heart's Multifunction Cardiogram (MCG); also known as 3DMP
Computerized EKG System) experimental and investigational
because the clinical value of the system in managing persons
suspected of having significant coronary artery disease has
not been established.
See
also CPB 0579 - T-Wave Alternans (../500_599/0579.html).
Background
Signal-Averaged Electrocardiography (SAECG):
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Signal-averaged electrocardiography (SAECG) is a technique
involving computerized analysis of segments of a standard
electrocardiogram that allows the detection of ventricular late
potentials. Ventricular late potentials in patients with cardiac
abnormalities, especially coronary artery disease or following
an acute myocardial infarction (MI), have been associated with
an increased risk of ventricular tachyarrhythmias and sudden
cardiac death. Proponents of SAECG claim that it can obviate
the need for invasive techniques commonly used to identify
high-risk patients for interventions that treat or prevent
ventricular tachyarrhythmia and sudden death.
An Agency for Healthcare Policy and Research's assessment
(AHCPR, 1998) found that the current data on SAECG show
relatively consistent high negative-predictive values, poor
positive-predictive values, and variable sensitivity and
specificity when the technique is used on patients with
cardiomyopathy or following a MI. However, the high
negative- predictive value of SAECG is largely due to the fact
that the incidence of fatal arrhythmic events among post-MI
patients is now below 10 %. The incidence of fatal
arrhythmias has declined among post-MI patients, a large
percentage of whom are on anti-thrombotic therapy, most
likely following the trend of decreased mortality rate following
MI.
In 1996, an American College of Cardiology (ACC) consensus
statement on SAECG concluded that SAECG has “established
value” in assessing the risk of development of sustained
ventricular arrhythmias in patients recovering from MI.
However, subsequently published guidelines from the ACC on
management of acute MI (1999) stated that the usefulness of
SAECG for risk assessment after MI is less well-established by
evidence/opinion. In addition, subsequently published ACC
guidelines on implantable anti-arrhythmia devices (1998) do
not recommend SAECG for selecting patients for automated
implantable cardioverter defibrillators (AICDs).
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Although it has been proposed that SAECG may be used to
select post-MI patients for anti-arrhythmic drugs or AICD
implantation, there are no prospective clinical studies
demonstrating the clinical utility of SAECG in selecting patients
for these therapies. In addition, there are no prospective
clinical studies proving that SAECG can be used successfully
to select patients for electrophysiologic studies or Holter
monitoring, or to use SAECG for risk stratification in lieu of
these other tests.
Grimm et al (2003) studied arrhythmia risk stratification with
regard to prophylactic implantable cardioverter-defibrillator
patients with in idiopathic dilated cardiomyopathy (IDC).
These researchers concluded that reduced left ventricular
ejection fraction (LVEF) and lack of beta-blocker use are
important arrhythmia risk predictors in IDC, whereas SAECG,
baroreflex sensitivity, heart rate variability, and T-wave
alternans do not seem to be helpful for arrhythmia risk
stratification. Furthermore, in a review on electrocardiographic
arrhythmia risk testing, Engel et al (2004) evaluated the
various electrocardiographic (ECG) techniques that appear to
have potential in assessment of risk for arrhythmia. The
resting ECG (premature ventricular contractions, QRS
duration, damage scores, QT dispersion, and ST segment and
T wave abnormalities), T-wave alternans, late potentials
identified on SAECG, and heart rate variability were explored.
The authors stated that unequivocal evidence to support the
widespread use of any single non-invasive technique is
lacking; further research in this area is needed.
Guidelines from the European Society for Cardiology
(Brignole, et al., 2004) concluded that the systematic use of
SAECG in syncope is “not recommended.”
Tamaki and colleagues (2009) prospectively compared the
predictive value of cardiac iodine-123
metaiodobenzylguanidine (MIBG) imaging for sudden cardiac
death (SCD) with that of the SAECG, heart rate variability
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(HRV), and QT dispersion in patients with chronic heart failure
(CHF). At entry, cardiac MIBG imaging, SAECG, 24-hr Holter
monitoring, and standard 12-lead ECG were performed in 106
consecutive stable CHF outpatients with a radionuclide
LVEF less than 40 %. The cardiac MIBG washout rate (WR)
was obtained from MIBG imaging. Furthermore, the time and
frequency domain HRV parameters were calculated from 24-hr
Holter recordings, and QT dispersion was measured from the
12-lead ECG. During a follow-up period of 65 +/- 31 months,
18 of 106 patients died suddenly. A multi-variate Cox analysis
revealed that WR and LVEF were significantly and
independently associated with SCD, whereas the SAECG,
HRV parameters, or QT dispersion were not. Patients with an
abnormal WR (greater than 27 %) had a significantly higher
risk of SCD (adjusted hazard ratio: 4.79, 95 % confidence
interval: 1.55 to 14.76). Even when confined to the patients
with LVEF greater than 35 %, SCD was significantly more
frequently observed in the patients with than without an
abnormal WR (p = 0.02). The authors concluded that cardiac
MIBG WR, but not SAECG, HRV, or QT dispersion, is a
powerful predictor of SCD in patients with mild-to-moderate
CHF, independently of LVEF.
Park and colleagues (2009) examined the correlation between
parameters of 2-dimensional ECG and SAECG in patients with
arrhythmogenic right ventricular cardiomyopathy (ARVC). A
total of 33 patients (13 females, 40.3 +/- 14.4 years old) were
included in this study. Both the right and left ventricular
dimensions and systolic function were assessed with
2-dimensional ECG. The SAECG was performed with high-
gain amplification and filtered using bi-directional Butterworth
filters between 40 and 250 Hz. The right ventricular (RV)
outflow tract was the most frequently (n = 18, 54 %) involved
segment. Six (18 %) patients had only mildly decreased RV
systolic function. All the other patients had normal RV systolic
function. Although localized left ventricular wall motion
abnormalities were observed in 14 (42 %) patients, the LVEF
was normal in most (n = 32, 97 %). Late potentials were
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positive in 22 (63 %) patients. There was no significant
correlation between parameters of the SAECG and
2-dimensional ECG for the entire patient population. The
authors concluded that the SAECG parameters exhibited no
correlation to any of 2-dimensional ECG parameters in the
patients with ARVC. Fragmented electrical activity may
develop with no significant relation to the anatomical changes
in the patients with ARVC.
The Agency for Healthcare Research and Quality's systematic
review of ECG-based signal analysis technologies for
evaluating patients with acute coronary syndrome (Coeytaux
et al, 2012) concluded that “Existing research is largely
insufficient to confidently inform the appropriate use of ECG-
based signal analysis technologies in diagnosing CAD and/or
ACS. Further research is needed to better describe the
performance characteristics of these devices to determine in
what circumstances, if any, these devices might precede,
replace, or add to the standard ECG in test strategies to
identify clinically significant CAD in the patient population of
interest. To fully assess the impact of these devices on
diagnostic strategies for patients with chest pain, test
performance needs to be linked to clinically important
outcomes through modeling or longitudinal studies”.
Proclemer et al (2013) examined the current clinical practice of
screening and risk evaluation for SCD in ischemic and non-
ischemic cardiomyopathy with a focus on selection of
candidates for ICD therapy, timing of ICD implantation, and
use of non-invasive and invasive diagnostic tests across
Europe. A systematic screening program for SCD existed in
19 out of 31 centers (61.3 %). Implantation of ICDs according
to the inclusion criteria of MADIT-II and SCD-HeFT trials was
reported in 30 and 29 % of centers, respectively, followed by
MADIT-CRT (18 %), COMPANION (16 %), and combined
MADIT and MUSTT (7 %) indications. In patients with severe
renal impairment, ICD implantation for primary prevention of
SCD was always avoided in 8 centers (33.3%), was not used
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only if creatinine level was greater than 2.5 mg/dL in 10
centers (32.2 %), and in patients with permanent dialysis in 8
centers (33.3 %). Signal-averaged electrocardiography and
heart rate variability were never considered as risk
stratification tools in 23 centers (74.2 %). Implantation of a
loop recorder was performed in patients with borderline
indications for ICD therapy in 6 centers (19.4 %), for research
purposes in 5 (16.1 %), and was never performed in 20 (64.5
%) centers. The authors concluded that the majority of
participating European centers have a screening program for
SCD and the selection of candidates for ICD therapy was
mainly based on the clinical risk stratification and not on non-
invasive and invasive diagnostic tests or implantable loop
recorder use.
Furthermore, an UpToDate review on “Clinical applications of
the signal-averaged electrocardiogram: Overview” (Narayan
and Cain, 2014) states that “Guideline Recommendations --
We agree with the 2008 American Heart Association
(AHA)/American College of Cardiology (ACC)/Heart Rhythm
Society (HRS) scientific statement on noninvasive risk
stratification and the 2006 ACC/AHA/European Society of
Cardiology (ESC) guidelines for management of patients with
ventricular arrhythmias, which concluded that the SAECG may
be useful to identify patients at low risk for SCD, but its routine
use to identify patients at high risk for SCD is not yet
adequately supported. Similarly, the 2006 AHA/ACC scientific
statement on syncope concluded that routine use of T-wave
alternans combined with signal-averaged ECG and
assessment of heart rate variability in patients with syncope
and a negative initial evaluation is not yet established and
currently is not indicated”.
An UpToDate review on “Use of the signal-averaged
electrocardiogram in nonischemic heart disease and cardiac
transplantation” (Narayan and Cain, 2015) concludes that:
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▪ Data are conflicting on the efficacy of SAECG in
predicting clinical outcome or ventricular arrhythmias in
patients with non-ischemic dilated cardiomyopathy.
▪ There are insufficient data to recommend the use of the
SAECG for risk stratification of patients with non-
ischemic cardiomyopathy.
▪ Although small studies have identified SAECG
alterations in patients with cardiac transplant rejection,
the utility of SAECG for detection of rejection has not
been established.
Dinov and colleagues (2016) correlated SAECG with the
endocardial scar characteristics in patients with ischemic
ventricular tachycardia (VT). These researchers suggested
that successful catheter ablation (CA) can result in
normalization of the SAECG. A total of 50 patients (42 men;
aged 67 ± 10 years, EF 34 ± 12 %) with ischemic VTs were
prospectively enrolled; SAECG was performed before and after
CA. Patients with at least 2 abnormal criteria (filtered
QRS greater than or equal to 114 ms; root mean square 40
less than 20 μV, and low-amplitude potentials 40 greater than
38 ms) were defined as having positive SAECG. There was a
linear correlation between endocardial scar area (less than 1.5
mV) and filtered QRS (r = 0.414; p = 0.003); CA resulted in
normalization of the SAECG in 6 patients. In patients with
filtered QRS less than or equal to 120 ms, 13 (40.6 %) patients
had normal SAECG after CA compared with 7 (21.9 %) before
ablation (p = 0.034). Patients with normal or normalized
SAECG after CA had better VT-free survival compared with
those whose SAECG remained abnormal. Abnormal SAECG
after CA was a predictor for VT recurrence: hazard ratio (HR)
= 3.64; p = 0.039 for the overall population, and HR = 5.80; p =
1.22 for patients having QRS less than or equal to 120 ms.
The authors concluded that there was a significant correlation
between the surface SAECG and endocardial scar size in
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patients with ischemic VTs. A successful CA could result in
normalization of SAECG that was associated with more
favorable long-term outcomes.
The main drawbacks of this study were its small sample size
(n = 50) and the relatively short follow-up (median of 12
months). The authors stated that this study should be
considered as a hypothesis-generating one. The presented
results are valid for patients with ischemic heart disease and
must be confirmed in other clinical conditions (e.g., dilated
cardiomyopathy, and arrhythmogenic right ventricular
dysplasia). They noted that as long as the post-ablation
SAECGs were recorded before the hospital discharge, it
remained unclear if the VT recurrences during the follow-up
were accompanied by perturbations in the SAECG. The
localization of the scar may influence the sensitivity of the
method because the abnormal low-amplitude potentials less
than 40 μV and root mean square voltage in the last 40 ms of
the filtered QRS were less pronounced in patients with anterior
or septal MIs.
Multifunction Cardiogram:
The Premier Heart digital database-driven multi-phase (3DMP)
electrocardiograph (EKG) System provides a computer
analysis of digitalized 12-lead EKG waveforms in the frequency
domain (power spectral estimate) to aid in the
detection of significant coronary artery disease. The 3DMP
system was cleared by the Food and Drugs Administration
(FDA) based on a 510(k) application. Weiss et al (2002)
reported on a cross-sectional analysis of the use of the 3DMP
system in 136 patients with symptoms of potential coronary
artery disease who were scheduled for angiography.
Originally, 200 patients were selected for the study, but 64 of
the patients were not included in the study because of various
technical problems in their 3DMP readings.
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Although the 3DMP system was positive for coronary artery
disease (CAD) in 76 of 78 patients with greater than 60 %
narrowing by angiography, the 3DMP system also read
positive in 8 of 12 patients with 40 to 60 % narrowing. None of
the 10 patients with greater than 0 to 40 % narrowing read as
positive by the 3DMP system, but 8 of 36 patients with 0 %
narrowing read as positive for CAD.
As a significant number (2 of 78) of patients with significant
angiographic lesions were missed by the 3DMP system, it is
not clear that the device is sufficiently accurate to either be
used in lieu of angiography or to select patients for
angiography.
There are no evidence-based guidelines from national
professional organizations that address the clinical utility of
3DMP in evaluating patients suspected of having coronary
artery disease. Prospective clinical studies are necessary to
demonstrate the clinical utility of the 3DMP system in
managing patients suspected of having significant coronary
artery disease.
A technology assessment prepared for the AHCPR on ECG-
based signal analysis technologies (Coeytaux et al, 2010)
stated that the reliability and test performance of 3DMP in
subjects at high-risk or with known CAD is promising. The
horizon scan identified 7 potentially relevant devices,
including 3 that use body surface mapping and 1 that uses
mathematical signal analysis. Of the 7 devices, only the
PRIME ECG by Heartscape Technologies (body surface
mapping) and the 3DMP/MCG/ mfEMT by Premier Heart
(mathematical signal analysis; referred to as the 3DMP) are
cleared for marketing by the FDA and commercially available.
One body surface mapping device (Visual ECG/Cardio3KG by
NewCardio) is commercially available but not cleared; the
other devices are not commercially available. The assessment
concluded: "There is currently little available evidence that
pertains to the utility of ECG-based signal analysis
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technologies as a diagnostic test among patients at low to
intermediate risk of CAD who present in the outpatient setting
with the chief complaint of chest pain. The limited evidence
that is available demonstrates proof of concept, particularly for
the PRIME ECG and 3DMP devices. Further research is
needed to better characterize the performance characteristics
of these devices to determine in what circumstances, if any,
these devices might precede, replace, or add to the standard
ECG for the diagnosis of CAD among patients who present
with chest pain in the outpatient setting. The randomized
controlled trial (RCT) study design is best suited for evaluating
the impact that ECG-based signal analysis technologies may
have on clinical decision-making and patient outcomes, but
there are indirect approaches that might be applied to answer
these questions".
Kawaji and colleagues (2015) stated that multifunction
cardiogram (MCG) is a computer-enhanced, resting
electrocardiogram analysis developed to detect
hemodynamically relevant CAD. Based on data from previous
studies suggesting excellent diagnostic accuracy in detecting
CAD, MCG (approved by the FDA) received a Current
Procedure Terminology (CPT) code in 2010 in United States.
However, there is no previous study validating MCG by using
fractional flow reserve (FFR) as the reference standard.
Multifunction cardiogram Evaluation in Diagnosis of Functional
coronary Ischemia sTudy (MED-FIT) was designed as a
single-center, prospective study enrolling 100 stable patients
with suspected CAD scheduled for coronary angiography. The
primary and secondary analyses evaluated the diagnostic
performance of the MCG severity score to detect functional
myocardial ischemia by FFR less than or equal to 0.80, and
angiographically significant coronary stenosis (percent
diameter stenosis greater than or equal to 50 %) by
quantitative coronary angiography. The current analysis set
consisted of 91 patients in whom MCG data with adequate
quality was obtained. The prevalence of positive functional
myocardial ischemia and angiographically significant stenosis
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in the current study was 42.7 % and 41.8 %, respectively.
Area under the receiver operating characteristics curve (AUC)
of the MCG severity score for functional myocardial ischemia
and angiographically significant stenosis was low (AUC 0.51,
95 % confidence interval [CI]: 0.38 to 0.63, and AUC 0.58, 95
% CI: 0.46 to 0.70, respectively). Sensitivity, and specificity of
the MCG severity score for functional myocardial ischemia and
angiographically significant stenosis was also low (32 %/67 %,
and 37 %/72 %) using a cut-off value of 4.0. The authors
concluded that diagnostic performance of the MCG severity
score was poor for both functional myocardial ischemia, and
angiographically significant stenosis.
CPT Codes / HCPCS Codes / ICD-10 Codes
Information in the [brackets] below has been added for clarification purposes. Codes requiring a 7th character are represented by "+":
Code Code Description
CPT codes not covered for indications listed in the CPB:
0206T Computerized database analysis of multiple
cycles of digitized cardiac electrical data from
two or more ECG leads, including transmission
to a remote center, application of multiple
nonlinear mathematical transformations, with
coronary artery obstruction severity assessment
93278 Signal-averaged electrocardiography (SAECG)
with or without ECG
Other CPT codes related to the CPB:
93000 -
93010
Electrocardiogram, routine ECG with at least 12
leads; with interpretation and report, tracing
only, without interpretation and report, or
interpretation and report only
ICD-10 codes not covered for indications listed in the CPB :
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Code Code Description
I05.0 - I52 Chronic rheumatic heart disease, hypertensive
disease, ischemic heart disease, diseases of
pulmonary circulation, and other forms of heart
disease
The above policy is based on the following references:
1. Cain ME, Anderson JL, Arnsdorf MF, et al. Signal-
averaged electrocardiography. ACC Expert Consensus
Document. JACC J Am Col Cardiol. 1996;27(1):238-249.
2. U.S. Department of Health and Human Services, Public
Health Service, Agency for Healthcare Policy and
Research (AHCPR). Signal-averaged
electrocardiography. Health Technology Assessment No.
11. AHCPR Pub. No. 98-0020. Rockville, MD: AHCPR;
May 1998.
3. Gregoratos G, Cheitlin MD, Conill A, et al. ACC/AHA
guidelines for implantation of cardiac pacemakers and
antiarrhythmia devices: A report of the American College
of Cardiology/American Heart Association Task Force on
Practice Guidelines (Committee on Pacemaker
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4. Ryan TJ, Antman EM, Brooks NH, et al. 1999 update:
ACC/AHA guidelines for the management of patients with
acute myocardial infarction. A report of the American
College of Cardiology/American Heart Association Task
Force on Practice Guidelines. J Am Coll Cardiol. 1999;34
(3):890-911.
5. Weiss MB, Narasimhadevara SM, Feng GQ, Shen
JT. Computer-enhanced frequency-domain and 12-lead
electrocardiography accurately detect abnormalities
consistent with obstructive and nonobstructive coronary
artery disease. Heart Dis. 2002;4(1):2-12.
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6. U.S. Food and Drug Administration (FDA), Center for
Devices and Radiologic Health (CDRH). Cardiotron
multi-phase EKG information analysis system. 510(k) no.
K992703. Rockville, MD: FDA; March 21, 2000.
7. Grimm W, Christ M, Bach J, et al. Noninvasive
arrhythmia risk stratification in idiopathic dilated
cardiomyopathy: Results of the Marburg Cardiomyopathy
Study. Circulation. 2003;108(23):2883-2891.
8. Engel G, Beckerman JG, Froelicher VF, et al.
Electrocardiographic arrhythmia risk testing. Curr Probl
Cardiol. 2004;29(7):365-432.
9. Hunt SA, Baker DW, Chin MH, et al. ACC/AHA guidelines
for the evaluation and management of chronic heart
failure in the adult. Bethesda, MD: American College of
Cardiology Foundation (ACCF); September 2001.
10. Husser D, Stridh M, Sornmo L, et al. Analysis of the
surface electrocardiogram for monitoring and predicting
antiarrhythmic drug effects in atrial fibrillation. Cardiovasc
Drugs Ther. 2004;18(5):377-386.
11. Priori SG, Aliot E, Blomstrom-Lundqvist C, et al. Task
Force on Sudden Cardiac Death of the European Society
of Cardiology. Eur Heart J. 2001;22(16):1374-450.
12. Brignole M, Alboni P, Benditt DG, et al. Guidelines on
management (diagnosis and treatment) of syncope--
update 2004. Europace. 2004;6(6):467-537.
13. Bennhagen RG, Sornmo L, Pahlm O, Pesonen E. Serial
signal-averaged electrocardiography in children after
cardiac transplantation. Pediatr Transplant. 2005;9
(6):773-779.
14. Jaroszynski AJ, Glowniak A, Sodolski T, et al. Effect of
haemodialysis on signal-averaged electrocardiogram
P-wave parameters. Nephrol Dial Transplant. 2006;21
(2):425-430.
15. Haghjoo M, Arya A, Parsaie M, et al. Does the abnormal
signal-averaged electrocardiogram predict future
appropriate therapy in patients with implantable
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cardioverter-defibrillators? J Electrocardiol. 2006;39
(2):150-155.
16. Horenstein MS, Idriss SF, Hamilton RM, et al. Efficacy of
signal-averaged electrocardiography in the young
orthotopic heart transplant patient to detect allograft
rejection. Pediatr Cardiol. 2006;27(5):589-593.
17. Omeroglu RE, Olgar S, Nisli K. Signal-averaged
electrocardiogram may be a beneficial prognostic
procedure in the postoperative follow-up tetralogy of fallot
patients to determine the risk of ventricular arrhythmias.
Pediatr Cardiol. 2007;28(3):208-212.
18. Schoenenberger AW, Erne P, Ammann S, et al.
Prediction of arrhythmic events after myocardial infarction
based on signal-averaged electrocardiogram and ejection
fraction. Pacing Clin Electrophysiol. 2008;31(2):221-228.
19. Grube E, Bootsveld A, Buellesfeld L, et al. Computerized
two-lead resting ECG analysis for the detection of
coronary artery stenosis after coronary revascularization.
Int J Med Sci. 2008;5(2):50-61.
20. Tamaki S, Yamada T, Okuyama Y, et al. Cardiac iodine-
123 metaiodobenzylguanidine imaging predicts sudden
cardiac death independently of left ventricular ejection
fraction in patients with chronic heart failure and left
ventricular systolic dysfunction: Results from a
comparative study with signal-averaged
electrocardiogram, heart rate variability, and QT
dispersion. J Am Coll Cardiol. 2009;53(5):426-435.
21. Park Y, Cho Y, Lee DY, et al. Correlation between the
parameters of signal-averaged ECG and two-dimensional
echocardiography in patients with arrhythmogenic right
ventricular cardiomyopathy. Ann Noninvasive
Electrocardiol. 2009;14(1):50-56.
22. Strobeck JE, Shen JT, Singh B, et al. Comparison of a
two-lead, computerized, resting ECG signal analysis
device, the MultiFunction-CardioGram or MCG (a.k.a.
3DMP), to quantitative coronary angiography for the
detection of relevant coronary artery stenosis (>70%) - a
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meta-analysis of all published trials performed and
analyzed in the US. Int J Med Sci. 2009;6(4):143-155.
23. Urbanova D, Urban L, Mikuskova E, et al. Frequency-
domain analysis of the signal-averaged
electrocardiogram in hematological malignancies
survivors. Bratisl Lek Listy. 2010;111(3):144-149.
24. Coeytaux RR, Williams JW, Chung E, Gharacholou M.
ECG-based signal analysis technologies. Technology
Assessment. Prepared for the Agency for Healthcare
Research and Quality (AHRQ) by the Duke Evidence-
based Practice Center (Contract No. HHSA 290-2007-
10066I). Rockville, MD: AHRQ; May 24, 2010.
25. Coeytaux RR, Leisy PJ, Wagner GS, et al. Systematic
review of ECG-based signal analysis technologies for
evaluating patients with acute coronary syndrome.
Agency for Healthcare Research and Quality's (AHRQ).
Rockville, MD; AHRQ; June 2012.
26. Proclemer A, Lewalter T, Bongiorni MG, et al; conducted
by the Scientific Initiative Committee, European Heart
Rhythm Association. Screening and risk evaluation for
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cardiomyopathy: Results of the European Heart Rhythm
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Copyright Aetna Inc. All rights reserved. Clinical Policy Bulletins are developed by Aetna to assist in administering plan
benefits and constitute neither offers of coverage nor medical advice. This Clinical Policy Bulletin contains only a partial,
general description of plan or program benefits and does not constitute a contract. Aetna does not provide health care
services and, therefore, cannot guarantee any results or outcomes. Participating providers are independent contractors
in private practice and are neither employees nor agents of Aetna or its affiliates. Treating providers are solely
responsible for medical advice and treatment of members. This Clinical Policy Bulletin may be updated and therefore is
subject to change.
Copyright © 2001-2018 Aetna Inc.
http://aetnet.aetna.com/mpa/cpb/600_699/0664.html 10/23/2018
AETNA BETTER HEALTH® OF PENNSYLVANIA
Amendment to Aetna Clinical Policy Bulletin Number: 0664 Signal-Averaged
Electrocardiography (SAECG)
For the Pennsylvania Medical Assistance plan: Signal-averaged electrocardiography (SAECG) w ith or without ECG may be considered for coverage on a case by case basis based on medical necessity.
www.aetnabetterhealth.com/pennsylvania new 11/01/2018